Introducing a new book to be published in late April 2026, "First Steps in Geospatial Data Science with Python". We are releasing a portion of the book ahead of its publication. The desire to "just ...

StatsPAI is a validation-tiered Python library for causal inference and applied econometrics. One import, 1,000+ registered functions across 80+ submodules (live count: python ...

Current Python alternatives for statistical models are slow, inaccurate and don't scale well. So we created a library that can be used to forecast in production environments or as benchmarks.

Emergency department (ED) boarding drives overcrowding, worsens outcomes, and strains hospital operations. Accurate short-term forecasts of boarding volumes can enable proactive resource management.

The Alfred P. Sloan Foundation awarded three Brown professors with early career research fellowships last week. The foundation named Assistant Professor of Mathematics Eric Larson, Assistant Professor ...

IS-MP-PC model can be used to better understand the dynamic of Monetary Policy Dynamics. The model has three elements to it. Consider a case where inflation expectations shifts to being higher than ...

As a student of economics and someone who has been building machine learning models as a data scientist, I’ve always been intrigued by the potential applications of machine learning in econometrics.

近年来，社会学科编程通常选择Python语言。Python有着易写、易懂、跨平台、用户群体大、线上资源丰富等优势。尽管如此，在实际学习过程中，非计算机专业的人士仍时常感到“专业不对口”：面对浩瀚的英文技术文档、大量的Python第三方文库，到底哪些才是我 ...

Linux has become increasingly popular for data analysis due to its stability and versatility. Econometrics and statistical analysis are fundamental to various fields such as economics, finance, ...

We have developed a practical and elegant closed-form option pricing formula for general GARCH models using a risk-neutral argument. To estimate the parameters, we propose a procedure and utilize ...